Features DX | What's
new in DX 8? | System Requirements | Further
Optimize your product or process with Design of Experiments (DOE)
Design-Expert® software, version 8 (DX8) offers features you won't
find anywhere else in an incredibly easy-to-use format. This
powerful program is a must for anyone wanting to improve a process
or a product. With Design-Expert you can screen for vital factors,
locate ideal process settings to achieve peak performance and
discover your optimal product formulations.
Design-Expert offers an impressive array of design options.
Design Expert 8 provides great flexibility to handle categorical
factors and allows them to be combined with mixture and/or process
variables. After building your design, generate worksheets with
your experiments laid out for you in randomized run-order. Add,
delete or duplicate runs in any design with the handy design
With annotated statistical analysis and an extensive
context-sensitive help system, you can easily interpret the
outputs. Interactive 2-D graphics support use of your mouse to
drag contours or set flags that display coordinates and predicted
responses. Rotatable 3-D plots make response visualization easy.
With the powerful optimization features in Design-Expert, you can
maximize desirability for dozens of responses simultaneously.
There are also unique tools for generating and graphing
propagation of error (POE), thus allowing you to achieve six-sigma
objectives for reducing variation. Maximize, minimize or hit
targets with factor levels set to give you robust results.
The upgrade to version 8 offers powerful new statistical tools,
such as upfront power calculation for factorial designs and the
Fraction of Design Space (FDS) graph for design evaluation. Other
new features for ease-of-use, functionality, and power add extra
appeal to a long-standing and well-loved program.
Powerful, Yet Easy to Use
Designed as a specialized DOE software package, Design-Expert 6
offers features for ease of use, functionality and power that you
won't find in general statistical packages. You'll discover a wide
variety of designs, the flexibility to modify designs, unique
evaluation capabilities, tools for response modeling, graphics to
simplify interpretation, multiple response optimization, POE
capabilities, an intuitive interface and a greatly expanded help
The factorial design builder makes it easy to
set up screening studies. Color-coded choices provide valuable
information on experiment resolution.
Crossed Mixture-Process Design - Seven Blends
(on Triangles) at Eight Process Combinations (Cube).
A Tremendous Variety of Designs Meet All Your Experimental Needs
- Standard two-level full and fractional factorials (up to 512
runs) for testing up to 21 factors simultaneously, now also with
minimum-aberration blocking choices
- General (multilevel) factorial designs (up to 32,000 runs)
using factors with mixed levels
- Taguchi orthogonal arrays
- High-resolution irregular fractions, such as 4 factors in 12
- Placket-Burman designs for 11, 19, 23, 27 or 31 factors in 12,
20, 24, 28, 32 or 64 runs respectively
- Min-Run Res IV (two-level factorial) designs for 5 to 50
factors: Screen main effects with maximum efficiency in terms of
- Response Surface Method (RSM) designs, including central
composite (small, face-centered, etc.), Box- Behnken (3-level),
hybrid and D-Optimal
- Mixture designs, such as simplex-lattice, simplex-centroid
screening (for up to 24 components) and D-optimal
- Combined mixture and process designs (mix your cake and bake
- Ability to graph any two columns of data on the XY graph (this
is a great way to view a blocked effect)
- Easy-to-use automatic or manual model reduction
- Ability to easily analyze designs with botched or missing data
High-powered mixture design and analysis
features lead you to optimal formulations.
Enjoy Incredible Flexibility in Design Modification
- Define your own generators for fractional factorial designs
- Impose linear multivariable constraints on RSM or mixture
- Add categorical factors to RSM, mixture or combined designs
- Create a factorial candidate set for RSM designs when only
specific factor levels are available
- Ignore a row of data while preserving the numbers
Build Confidence with Statistical Analysis of Data
- If your model is aliased, a warning will pop up prior to
viewing the ANOVA for two-level fractional factorials, allowing
you to make substitutions for aliased effects
- Select optional annotated views for assistance interpreting
- Inspect F-test values on individual model terms and confidence
intervals on coefficients
- Automatically select effects using Lenth's criteria or
- Take advantage of new user preferences, for example, make a
global change in the significance threshold (0.05 by default vs.
0.01 and 0.1)
Take Advantage of Powerful Tools for Response Modeling
- Change models from RSM to factorial and back and from Scheffe
(mixture) to slack (during design building and at model
- Add integer power terms to the model, for example, quartic
- Select terms for model, error, or to be ignored (allows
analysis of split-plot and nested designs)
Simplify Interpretation with Terrific Graphics
- A quick summary of the design type as well as factor, response
and model information is available by clicking on the design
- Discover significant effects at a glance with half-normal or
normal probability plots, made easier by including points
representing estimates of pure error (if available from your
- See the Box-Cox plot for advice on the best response
- View a complete array of diagnostic graphs to check
statistical assumptions and detect possible outliers (bonus
feature: predicted-versus-actual graphs with a 45º line)
- Graph alternative aliased interactions
- See the effects plot in the original scale after transforming
- Observe variation in predictions by viewing the least
significant difference (LSD) bars on the model graphs
- Poorly predicted regions on contour maps are shaded to give
you confidence in your predictions
- Slice your contour plots using a simple slide bar (and see
actual design points when they're on a slice!)
- Set flags to reveal the predicted response at any location
- Drag 2-D contours using your mouse
- Rotate 3-D graphics and see projected 2-D contours
- Edit colors, text and more to produce professional reports
- See all effects on one graph with trace and perturbation plots
- Plot the standard error of your design on any graph type
(contour, 3-D, etc.)
Brilliant graphics help you visualize response
surface optimization. Real-time rotation allows fast viewing
with minimal effort.
Vital factors pop out on Half-Normal Plots.
Discover critical interactions affecting your product or
Drag contours and set flags to predict
responses at any combination of factors.
Locate Your Sweet Spot with Multiple Response Optimization
- Maximize, minimize or target specific levels for both
responses and factors
- Set weight and importance levels to prioritize responses for
- Choose 2-D contour, 3-D surface, histogram or ramp
- Include categorical factors
- Set factors at constant levels
- Add equation-only responses, such as cost, to the optimization
- Look at the overlay plot to view constraints on your process
- Predict responses at any set of conditions (including
- Discover optimal process conditions or formulations
Achieve "Six-Sigma" Goals
- Explore propagation of error (POE) for mixtures, crossed
designs and transformed responses, as well as RSM
- For purposes of POE, enter your own response standard
deviation or set it at zero
Save Time with Design-Expert's Intuitive Interface
- Easily maneuver through the program: down trees, through
wizards, and across progressive toolbars
- Quickly select the next step with incredibly easy-to-use
- Open reports and graphs for automatic updating
- View numerical outputs spreadsheet style
- Cut and paste graphics to your word processor or presentation,
or numbers to and from a spreadsheet
- Export any grid view as ASCII text, for example, design
layouts or ANOVA reports
- View several graphs simultaneously using the handy pop-out
- 32-bit architecture provides maximum performance on Windows
95, 98, 2000, NT and beyond
- Access graphic and spreadsheet options instantly with a simple
- Choose significant terms to plot from the pull-down list on
the Factors Tool
Find the Answers to your Questions in the Expanded Help System
- Greatly improved context-sensitive help provides immediate
- Better guidance helps you choose the best model
- A bonus help section provides "quick start" advice to novices
- Special user tips offer hints not normally found in help
Interactions like this are often the key to
breakthrough discoveries. Go for the maximum combination or
find the flats for robust operation.
Graphical optimization shows clear windows for
multiple response optimization.
New graphics and improved interface
- Half-normal selection of important effects on all factorial
Simple and robust method for selecting important effects
formerly available only for two-level designs. For example, the
screen shot to the right is from an experiment on 5 woods glued
with 5 adhesives, using 2 applicators with 4 clamps at 2
pressures. The vital effects become apparent at a glance!
*(Detailed in "Graphical Select-ion of Effects in General
Factorials"winner of the Shewell Award for best presentation at
the 2007 Fall Technical Conference, co-sponsored by the American
Society for Quality and the American Statistical Association.)
- Smoother color gradations on 2D contours: More impressive for
presentations to management, clients, or colleagues.
- Rounded contour values: More presentable defaults requiring
less 'fiddling' for reporting purposes.
- Plant flags on 3D surfaces: Previously, you could only put
flags on 2D contour plots. To the right we see a flag planted by
numerical optimization on turbidity of a detergent formulation
via mixture design a specialized application of response
surface methods (RSM).
- New and fully configurable mesh option that reflects smooth,
lighted colors off your 3D surface: Dazzle your customers and
colleagues while providing highly-informative graphics showing
how responses will react to process changes. (Mesh can be turned
off if you like.)
- 3D graphs that you can spin with your mouse: When you see your
cursor turn into a hand (I), simply grab and rotate!
Double-click the graph to go back to the starting angle.
- Push-button averaging on the factors tool: Provides far easier
main effects plotting and makes interactions more meaningful.
Previously, the only option to average factors came via a hidden
drop-list. The screen shot series at right shows the result of
simply pressing the "Avg" for 5 woods glued with 5 adhesives
using 2 applicators at 2 pressures. This causes the least
significant difference (LSD) bars to shrink, revealing an
important difference between two particular clamps.
- More-interactive cube plots: Click on design points to see
factor levels and response predictions on graph legends, as
- Direct setting of discrete (fixed) numeric levels in response
surface designs: Limit factor settings to reasonable levels but
still produce continuous models. The example to the right shows
that 3 battery types must be tested at 3 discrete temperatures.
Previously, this would have been possible but very tricky via a
work-around. Now it's easy!
- Discrete factor levels adhered to in numeric optimization:
Find the most desirable setting for factors that are not
continuous, such as the number of passes through a spray coater.
- Enter input variables vertically (as shown above): When
entering many levels, this may be more convenient than the
- Reference lines on plots: Horizontal, vertical, and free
style-lines enhance plots. At the right it becomes completely
clear that four clamps tested for a wood-adhesive application
fall into two distinct groups acceptable versus not
acceptable, based on a cutoff of 50.
- Predicted vs. Actual graph availability in Model Graphs, not
just in Diagnostics: This is useful when a response has been
transformed because in Model Graphs mode, you can change the
view back to the more relevant original scale.
- Confidence, prediction, and tolerance intervals (CI, PI &
TI) plotted with configurable colors in one-factor response
plots: Convey prediction uncertainties via bands around the best
fit. The screen shot at right shows actual run results
represented as red circles. The solid line is the predicted
value based on the polynomial model. The bands are the CI
(narrowest), PI, and TI (widest).
- Color-coded response surface graphs show where standard error
increases: This makes it easier to understand why a predicted
response will get you in trouble by extrapolating beyond actual
experimentation regions. The example at right shows a flag set
beyond the axial points of a central composite design-making the
Better mixture design and modeling tools
- Partial quadratic mixture (PQM) analysis: Model non-linear
blending behavior most effectively. The example at right shows
an orange drink formulated using artificial flavorings. Primary
taste intensity, as measured by a sensory panel, proves to be
non-linear in a way that is modeled best using PQM.
- Design for linear plus squared terms in mixture models: Reduce
the number of blends required for optimally-designed experiments
that reveal non-linear blending.
- Design for special and full quartic mixture models: Capture
extremely non-linear relationships among all components.
- Blocking expanded to simplex mixture designs: For example,
blend your cakes and bake them in two oven batches.
- Trace plot options show end points as actual values when
building designs using U-pseudo coding: The upper ("U") bounded
approach is advantageous when inverting regions in certain
constrained mixture situations. However, due to axis flipping,
it's easy to misinterpret trends when viewing a trace plot
without this new feature.
- Increased limit on components for screening and historical*
designs. Design-Expert now handles up to 50 individual
ingredients up from 40 and 24, respectively.
*(An example is happenstance data collected by assaying retained
samples from a period of material production.)
More choices when custom-designing your experiment
- D-, IV-, and A-optimal design selection: New and expanded
criteria when crafting experiments to models of choice within
- Constraints calculator: Simplifies derivation of constraint
inequalities. At right, food scientists cooking starch must bake
it longer at low temperatures. With program Help guidance, the
design space's lower left corner can be excluded using a
multilinear constraint equation generated from a few user
inputs. An optimal design is then fitted to this region.
- Tolerance-interval-based design sizing: Enhances your fraction
of design space (fds) plots to assess whether your planned
experiment is large enough, given the underlying variability
(noise), to establish tolerances within the acceptable range.
Additional statistics and more concise reporting of vital
- Improved curvature testing for factorials with center points:
All design points are now fitted to the polynomial model used
for predictions. This provides a more realistic impact of
significant non-linear response behavior. Diagnostics can be
done for the model adjusted for curvature or, via a view option,
unadjusted. Models without a term for curvature (unadjusted) are
used for model graph and point predictions.
- Coefficients summary: After modeling your response(s), see a
concise table of coefficients that's color-coded by relative
significance. Below, the second response is modeled only by main
effects, two being significant at the p<0.1 level.
- Condensed "Fit Summary" table: See vital details on model
choices before delving into all the particulars. Below you can
see why the program recommends one model over others (note the
superior R-squared values for quadratic).
- Tolerance interval (TI) estimates on point prediction: This is
important for verification studies to ensure your process stays
within manufacturing specifications. For example, the TI shown
below provides assurance that thickness will remain within a
required range of 4400 to 4600.
Increased visibility and versatility of tools and features
- Many new, high-visibility tools: Options previously available
via hidden View menu options are now easily seen and capitalized
upon. The Design Tool shown 'floating' on the screen shot below
is one example.
- Design layout column widths now adjust automatically by
double-clicking column-header boundaries: Multiple columns
- Attach row comments by right-clicking on row headers: A handy
way to record important observations, as shown below.
- Topic Help, Tutorials, and Sample Files now also reside in the
main Help menu: Follow these alternate paths for getting timely
- Screen Tips is now a main menu item ("Tips"): Great visibility
and easy access to very useful just-in-time advice, shown below.
- Response surface method (RSM) models can be fitted with
factors in their actual levels: This enables no-intercept model
Enhanced design evaluation
- Several new matrix measures are now provided: Most notable is
the G-efficiency. (This criterion, expressed on a 0 to 100
percent scale with higher being better, leads to designs that
generate more consistent variance of your predicted response.
However, like any other single measure, it may not accurately
reflect the overall effectiveness of a particular matrix. That's
why Design-Expert provides an array of matrix statistics and
graphics for overall design evaluation.)
- Fraction of paired design space (FPDS): This resourceful tool
lets you assess the power of RSM or mixture designs to detect
specified signals (response differences judged important) in the
presence of noise (system-standard deviation). At right, less
than half the design space reveals the difference of interest.
Ideally, this exceeds 80 percent, so here the experimenter
should consider adding more runs to the design.
- New, powerful tools for multiple response optimization:
Options include standard error models. All else equal, choose
system settings in regions predicted to exhibit the highest
Many things made nicer, easier faster throughout the program
- One-click updates: Check for free releases with one press
(shown at right) and download them directly.
- Better defaults and tick marks: Nicely rounded values provide
presentable graphs straight away.
- Zoom up graphs with your mouse wheel (a right-click resets to
original size): Quickly zero in on regions of interest.
- Hold down your left mouse button to drag graphs into various
positions (a right-click resets original placement): It's a fast
way to situate the region of interest where you want it in the
coordinate space. Components G and H in the mixture trace plot
at right are constrained to very tight ranges relative to other
ingredients. They are hardly visible without first zooming and
then dragging the intersection (the overall centroid of the
formulation space) to the middle.
- Separate preference tabs for X-Y versus surface graphs: DX8
delivers plotting and graphing simplicity.
- Reduced graph-updating flicker: Now it's less distracting when
you redraw responses at varying input-variable levels.
- Categoric factors (established via general factorials, for
example) are now convertible to discrete numerics: This lets you
apply response surface methodologies while adhering to processes
that run most conveniently only at specific settings.
- Color-by-point-type added to graph columns: Very useful
addition to scatter-plots, such as this one below for a central
composite design (CCD).
- Upgraded MFC (Microsoft Foundation Class) common controls:
This new application framework provides an improved look and
- XML utility offers new script feature that lists all possible
commands. You can parse files with extensions other than .xml.
It also provides new import/export/reset-preference commands:
More power to operate Design-Expert programmatically.
||Display Resolution 800x600 or greater
||Windows XP SP3, Vista SP2, Windows 7
SP1 or Windows 8
||Pentium III 800 MHz (Pentium IV 1 GHz or
||min. 256 MB RAM (Windows XP)
min. 512 MB (Windows Vista, Windows 7 or Windows 8)
||50 MB or more of free hard disk space